Generally, a pipeline system provides a continuous pipe conduit that may include a variety of components and equipment, e.g., valves, compressor stations, communications systems, and meters. A pipeline may be used to transport liquid or gaseous materials from one point to another, usually from one point (or points) of production or processing to another, or to points of use. For example, an air separation unit may be used to separate atmospheric air into gaseous components (e.g., oxygen gas (O2) nitrogen gas (N2) hydrogen gas (H2), Argon gas (Ar), etc.) At compressor stations, compressors maintain the pressure of the material in the pipeline as it is transported from one site to another. Similarly, for a liquid bearing pipeline, pumps may be used to introduce and maintain pressure for a liquid substance transported by the pipeline.
Obviously, running and maintaining a pipeline system can be expensive and complex, and the operations of a pipeline system are frequently coordinated and controlled from a central operations control center. At such a control center, an operator may monitor the operational state of the pipeline, and each of its constituent elements. To perform this task, software applications are available that monitor the operational state of pipeline components, including compressors and pumps, valves, segments, etc. Sensors affixed to these (and other) field devices are configured to relay information regarding a then current state of the device to the control center. A real-time status database is used to capture this information and make it available to the relevant individuals at the control center. In some cases, the monitoring systems may be configured to raise an alarm when a monitored parameter (or combination of parameters) falls below (or climbs above) a predetermined value.
Other complex industrial systems and processes use a similar approach. For example, a petroleum refinery (at one end of a pipeline) may be monitored from a central control center using a real-time status database configured to receive data collected from the field devices of the refinery. Fleet management applications used to monitor the location and status of a fleet of delivery vehicles provide another example of a large complex operation that may be monitored from a central control center using a real-time status database.
For these systems, a central concern is the ongoing operational state of the system at any given point in time, and the real-time status database is an effective tool for monitoring this. Frequently however, system operators need access to not just the current status available from the real-time database, but also need access to historical data regarding the operational state of the system. Such information may be needed for a variety of purposes, including, for example, optimizing system operations, understanding the impact of changes over time, ensuring regulatory compliance, and many other applications. Accordingly, the control center for a pipeline (or other industrial system) may include a “historian database,” or more simply, a “historian.” A historian is used to archive values from the real-time status database for the monitored field devices. That is, while the real-time status database may record the current pressure at a given pipeline location, the historian may store what the same value was a minute, hour, day week, or even years ago. The historian may be queried for historical values by the relevant individuals at the control center.
Ideally, whenever any value in the real-time database changes, the previous value should be archived by the historian. Additionally, some values may need to be archived at regular intervals, regardless of whether the value has changed. However, pipeline systems are large and complex with hundreds, if not thousands, of monitored field devices, and thousands, if not tens-of-thousands, of monitored parameters. Other large industrial operations may be similarly complex. Given the scope of these types of industrial operations, the amount of data pushed from the real-time database to the historian may be enormous. If the historian cannot keep up, data values for some points in time may be lost. Some currently available historian applications address this issue by limiting the volume of historical data that may be archived by the historian. Other historians may be configured to use a “best effort” approach, and archive as much data as it can, but to drop data when it is pushed to the historian at a sufficient rate. In either case, the archived data may not be suitably comprehensive for some purposes. Additionally, due to the enormous amount of process data some plants produce, a historian may be configured to store data offline, (i.e., apart from the system running the historian itself). However, such an approach may lead to unacceptable delays when the operator wishes to query the historian to retrieve historical operational state data for the monitored system.
Accordingly, comprehensively capturing data in a historian, and making this information available to a system operator, is a difficult task. Therefore, there remains a need for techniques for managing a historian in large, complex industrial operations such as a pipeline.